Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/17644#discussion_r116432122
--- Diff:
sql/hive/src/main/scala/org/apache/spark/sql/hive/client/HiveClientImpl.scala
---
@@ -408,9 +425,9 @@ private[hive] class HiveClientImpl(
},
schema = schema,
partitionColumnNames = partCols.map(_.name),
- // We can not populate bucketing information for Hive tables as
Spark SQL has a different
- // implementation of hash function from Hive.
- bucketSpec = None,
+ // For data source tables, we will always overwrite the bucket
spec in
--- End diff --
Sorry I made a mistake. This is true even for hive tables.
If the table is written by Spark, we will put bucketing information in
table properties, and will always overwrite the bucket spec in hive metastore
by the bucketing information in table properties. This means, if we have bucket
spec in both hive metastore and table properties, we will trust the one in
table properties.
let's update this document.
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